Bank Marketing Data Set

Dataset statistics

Number of variables	21
Number of observations	26916
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	4.3 MiB
Average record size in memory	168.0 B

Variable types

Categorical	10
Numeric	10
Boolean	1

Warnings

`pdays` is highly correlated with `previous`	High correlation
`previous` is highly correlated with `pdays` and 1 other fields	High correlation
`emp.var.rate` is highly correlated with `cons.price.idx` and 2 other fields	High correlation
`cons.price.idx` is highly correlated with `emp.var.rate` and 1 other fields	High correlation
`euribor3m` is highly correlated with `emp.var.rate` and 2 other fields	High correlation
`nr.employed` is highly correlated with `previous` and 2 other fields	High correlation
`pdays` is highly correlated with `previous`	High correlation
`previous` is highly correlated with `pdays`	High correlation
`emp.var.rate` is highly correlated with `cons.price.idx` and 2 other fields	High correlation
`cons.price.idx` is highly correlated with `emp.var.rate`	High correlation
`euribor3m` is highly correlated with `emp.var.rate` and 1 other fields	High correlation
`nr.employed` is highly correlated with `emp.var.rate` and 1 other fields	High correlation
`age` is highly correlated with `pdays` and 1 other fields	High correlation
`duration` is highly correlated with `pdays` and 1 other fields	High correlation
`campaign` is highly correlated with `pdays` and 1 other fields	High correlation
`pdays` is highly correlated with `age` and 3 other fields	High correlation
`previous` is highly correlated with `age` and 3 other fields	High correlation
`emp.var.rate` is highly correlated with `euribor3m`	High correlation
`euribor3m` is highly correlated with `emp.var.rate`	High correlation
`loan` is highly correlated with `housing`	High correlation
`cons.conf.idx` is highly correlated with `cons.price.idx` and 7 other fields	High correlation
`cons.price.idx` is highly correlated with `cons.conf.idx` and 6 other fields	High correlation
`euribor3m` is highly correlated with `cons.conf.idx` and 5 other fields	High correlation
`poutcome` is highly correlated with `cons.conf.idx` and 6 other fields	High correlation
`month` is highly correlated with `cons.conf.idx` and 5 other fields	High correlation
`subcribed` is highly correlated with `cons.conf.idx` and 1 other fields	High correlation
`contact` is highly correlated with `cons.price.idx` and 3 other fields	High correlation
`job` is highly correlated with `education` and 1 other fields	High correlation
`education` is highly correlated with `job`	High correlation
`nr.employed` is highly correlated with `cons.conf.idx` and 8 other fields	High correlation
`pdays` is highly correlated with `cons.conf.idx` and 3 other fields	High correlation
`age` is highly correlated with `job`	High correlation
`housing` is highly correlated with `loan`	High correlation
`previous` is highly correlated with `poutcome` and 1 other fields	High correlation
`emp.var.rate` is highly correlated with `cons.conf.idx` and 6 other fields	High correlation
`contact` is highly correlated with `month`	High correlation
`loan` is highly correlated with `housing`	High correlation
`housing` is highly correlated with `loan`	High correlation
`month` is highly correlated with `contact`	High correlation
`previous` has 23042 (85.6%) zeros	Zeros

Reproduction

Analysis started	2021-08-08 16:12:37.742619
Analysis finished	2021-08-08 16:13:22.808811
Duration	45.07 seconds
Software version	pandas-profiling v3.0.0
Download configuration	config.json

education
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	210.4 KiB

university.degree	12164
high.school	9512
professional.course	5240

Length

Max length	19
Median length	17
Mean length	15.26898499
Min length	11

Characters and Unicode

Total characters	410980
Distinct characters	19
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	high.school
2nd row	high.school
3rd row	high.school
4th row	professional.course
5th row	professional.course

Common Values

Value	Count	Frequency (%)
university.degree	12164	45.2%
high.school	9512	35.3%
professional.course	5240	19.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
university.degree	12164	45.2%
high.school	9512	35.3%
professional.course	5240	19.5%

Most occurring characters

Value	Count	Frequency (%)
e	59136	14.4%
i	39080	9.5%
s	37396	9.1%
r	34808	8.5%
o	34744	8.5%
h	28536	6.9%
.	26916	6.5%
g	21676	5.3%
n	17404	4.2%
u	17404	4.2%
Other values (9)	93880	22.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	384064	93.5%
Other Punctuation	26916	6.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	59136	15.4%
i	39080	10.2%
s	37396	9.7%
r	34808	9.1%
o	34744	9.0%
h	28536	7.4%
g	21676	5.6%
n	17404	4.5%
u	17404	4.5%
c	14752	3.8%
Other values (8)	79128	20.6%

Other Punctuation

Value	Count	Frequency (%)
.	26916	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	384064	93.5%
Common	26916	6.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	59136	15.4%
i	39080	10.2%
s	37396	9.7%
r	34808	9.1%
o	34744	9.0%
h	28536	7.4%
g	21676	5.6%
n	17404	4.5%
u	17404	4.5%
c	14752	3.8%
Other values (8)	79128	20.6%

Common

Value	Count	Frequency (%)
.	26916	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	410980	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	59136	14.4%
i	39080	9.5%
s	37396	9.1%
r	34808	8.5%
o	34744	8.5%
h	28536	6.9%
.	26916	6.5%
g	21676	5.3%
n	17404	4.2%
u	17404	4.2%
Other values (9)	93880	22.8%

age
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	71
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	38.80067618

Minimum	18
Maximum	91
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	210.4 KiB

Quantile statistics

Minimum	18
5-th percentile	26
Q1	31
median	37
Q3	45
95-th percentile	57
Maximum	91
Range	73
Interquartile range (IQR)	14

Descriptive statistics

Standard deviation	9.732536154
Coefficient of variation (CV)	0.2508341893
Kurtosis	0.3457418685
Mean	38.80067618
Median Absolute Deviation (MAD)	6
Skewness	0.7731945695
Sum	1044359
Variance	94.72225999
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
31	1466	5.4%
32	1435	5.3%
33	1376	5.1%
30	1330	4.9%
34	1276	4.7%
35	1262	4.7%
36	1207	4.5%
29	1149	4.3%
37	1092	4.1%
39	922	3.4%
Other values (61)	14401	53.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
18	5	< 0.1%
19	4	< 0.1%
20	37	0.1%
21	64	0.2%
22	82	0.3%
23	159	0.6%
24	331	1.2%
25	423	1.6%
26	504	1.9%
27	611	2.3%

Value	Count	Frequency (%)
91	2	< 0.1%
88	2	< 0.1%
86	1	< 0.1%
85	2	< 0.1%
84	1	< 0.1%
83	5	< 0.1%
82	7	< 0.1%
81	5	< 0.1%
80	5	< 0.1%
79	3	< 0.1%

job
Categorical

HIGH CORRELATION

Distinct	12
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	210.4 KiB

admin.	9442
technician	5998
services	3071
management	2450
blue-collar	1425
Other values (7)	4530

Length

Max length	13
Median length	8
Mean length	8.434351315
Min length	6

Characters and Unicode

Total characters	227019
Distinct characters	24
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	services
2nd row	services
3rd row	services
4th row	admin.
5th row	technician

Common Values

Value	Count	Frequency (%)
admin.	9442	35.1%
technician	5998	22.3%
services	3071	11.4%
management	2450	9.1%
blue-collar	1425	5.3%
self-employed	1051	3.9%
entrepreneur	979	3.6%
retired	801	3.0%
unemployed	663	2.5%
student	570	2.1%
Other values (2)	466	1.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
admin	9442	35.1%
technician	5998	22.3%
services	3071	11.4%
management	2450	9.1%
blue-collar	1425	5.3%
self-employed	1051	3.9%
entrepreneur	979	3.6%
retired	801	3.0%
unemployed	663	2.5%
student	570	2.1%
Other values (2)	466	1.7%

Most occurring characters

Value	Count	Frequency (%)
n	29811	13.1%
e	29404	13.0%
i	25682	11.3%
a	22137	9.8%
c	16492	7.3%
m	16428	7.2%
d	12899	5.7%
t	11368	5.0%
.	9442	4.2%
r	9035	4.0%
Other values (14)	44321	19.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	215101	94.8%
Other Punctuation	9442	4.2%
Dash Punctuation	2476	1.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	29811	13.9%
e	29404	13.7%
i	25682	11.9%
a	22137	10.3%
c	16492	7.7%
m	16428	7.6%
d	12899	6.0%
t	11368	5.3%
r	9035	4.2%
s	8135	3.8%
Other values (12)	33710	15.7%

Other Punctuation

Value	Count	Frequency (%)
.	9442	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	2476	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	215101	94.8%
Common	11918	5.2%

Most frequent character per script

Latin

Value	Count	Frequency (%)
n	29811	13.9%
e	29404	13.7%
i	25682	11.9%
a	22137	10.3%
c	16492	7.7%
m	16428	7.6%
d	12899	6.0%
t	11368	5.3%
r	9035	4.2%
s	8135	3.8%
Other values (12)	33710	15.7%

Common

Value	Count	Frequency (%)
.	9442	79.2%
-	2476	20.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	227019	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
n	29811	13.1%
e	29404	13.0%
i	25682	11.3%
a	22137	9.8%
c	16492	7.3%
m	16428	7.2%
d	12899	5.7%
t	11368	5.0%
.	9442	4.2%
r	9035	4.0%
Other values (14)	44321	19.5%

marital
Categorical

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	210.4 KiB

married	14703
single	8976
divorced	3186
unknown	51

Length

Max length	8
Median length	7
Mean length	6.784886313
Min length	6

Characters and Unicode

Total characters	182622
Distinct characters	16
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	married
2nd row	married
3rd row	married
4th row	married
5th row	single

Common Values

Value	Count	Frequency (%)
married	14703	54.6%
single	8976	33.3%
divorced	3186	11.8%
unknown	51	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
married	14703	54.6%
single	8976	33.3%
divorced	3186	11.8%
unknown	51	0.2%

Most occurring characters

Value	Count	Frequency (%)
r	32592	17.8%
i	26865	14.7%
e	26865	14.7%
d	21075	11.5%
m	14703	8.1%
a	14703	8.1%
n	9129	5.0%
s	8976	4.9%
g	8976	4.9%
l	8976	4.9%
Other values (6)	9762	5.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	182622	100.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
r	32592	17.8%
i	26865	14.7%
e	26865	14.7%
d	21075	11.5%
m	14703	8.1%
a	14703	8.1%
n	9129	5.0%
s	8976	4.9%
g	8976	4.9%
l	8976	4.9%
Other values (6)	9762	5.3%

Most occurring scripts

Value	Count	Frequency (%)
Latin	182622	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
r	32592	17.8%
i	26865	14.7%
e	26865	14.7%
d	21075	11.5%
m	14703	8.1%
a	14703	8.1%
n	9129	5.0%
s	8976	4.9%
g	8976	4.9%
l	8976	4.9%
Other values (6)	9762	5.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	182622	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
r	32592	17.8%
i	26865	14.7%
e	26865	14.7%
d	21075	11.5%
m	14703	8.1%
a	14703	8.1%
n	9129	5.0%
s	8976	4.9%
g	8976	4.9%
l	8976	4.9%
Other values (6)	9762	5.3%

default
Categorical

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	210.4 KiB

no	23049
unknown	3864
yes	3

Length

Max length	7
Median length	2
Mean length	2.717900134
Min length	2

Characters and Unicode

Total characters	73155
Distinct characters	8
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	unknown
2nd row	no
3rd row	no
4th row	no
5th row	no

Common Values

Value	Count	Frequency (%)
no	23049	85.6%
unknown	3864	14.4%
yes	3	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
no	23049	85.6%
unknown	3864	14.4%
yes	3	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
n	34641	47.4%
o	26913	36.8%
u	3864	5.3%
k	3864	5.3%
w	3864	5.3%
y	3	< 0.1%
e	3	< 0.1%
s	3	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	73155	100.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	34641	47.4%
o	26913	36.8%
u	3864	5.3%
k	3864	5.3%
w	3864	5.3%
y	3	< 0.1%
e	3	< 0.1%
s	3	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	73155	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
n	34641	47.4%
o	26913	36.8%
u	3864	5.3%
k	3864	5.3%
w	3864	5.3%
y	3	< 0.1%
e	3	< 0.1%
s	3	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	73155	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
n	34641	47.4%
o	26913	36.8%
u	3864	5.3%
k	3864	5.3%
w	3864	5.3%
y	3	< 0.1%
e	3	< 0.1%
s	3	< 0.1%

housing
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	210.4 KiB

yes	14269
no	12025
unknown	622

Length

Max length	7
Median length	3
Mean length	2.645675435
Min length	2

Characters and Unicode

Total characters	71211
Distinct characters	8
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	no
2nd row	yes
3rd row	no
4th row	no
5th row	yes

Common Values

Value	Count	Frequency (%)
yes	14269	53.0%
no	12025	44.7%
unknown	622	2.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
yes	14269	53.0%
no	12025	44.7%
unknown	622	2.3%

Most occurring characters

Value	Count	Frequency (%)
y	14269	20.0%
e	14269	20.0%
s	14269	20.0%
n	13891	19.5%
o	12647	17.8%
u	622	0.9%
k	622	0.9%
w	622	0.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	71211	100.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
y	14269	20.0%
e	14269	20.0%
s	14269	20.0%
n	13891	19.5%
o	12647	17.8%
u	622	0.9%
k	622	0.9%
w	622	0.9%

Most occurring scripts

Value	Count	Frequency (%)
Latin	71211	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
y	14269	20.0%
e	14269	20.0%
s	14269	20.0%
n	13891	19.5%
o	12647	17.8%
u	622	0.9%
k	622	0.9%
w	622	0.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	71211	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
y	14269	20.0%
e	14269	20.0%
s	14269	20.0%
n	13891	19.5%
o	12647	17.8%
u	622	0.9%
k	622	0.9%
w	622	0.9%

loan
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	210.4 KiB

no	22128
yes	4166
unknown	622

Length

Max length	7
Median length	2
Mean length	2.270322485
Min length	2

Characters and Unicode

Total characters	61108
Distinct characters	8
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	no
2nd row	no
3rd row	yes
4th row	no
5th row	no

Common Values

Value	Count	Frequency (%)
no	22128	82.2%
yes	4166	15.5%
unknown	622	2.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
no	22128	82.2%
yes	4166	15.5%
unknown	622	2.3%

Most occurring characters

Value	Count	Frequency (%)
n	23994	39.3%
o	22750	37.2%
y	4166	6.8%
e	4166	6.8%
s	4166	6.8%
u	622	1.0%
k	622	1.0%
w	622	1.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	61108	100.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	23994	39.3%
o	22750	37.2%
y	4166	6.8%
e	4166	6.8%
s	4166	6.8%
u	622	1.0%
k	622	1.0%
w	622	1.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	61108	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
n	23994	39.3%
o	22750	37.2%
y	4166	6.8%
e	4166	6.8%
s	4166	6.8%
u	622	1.0%
k	622	1.0%
w	622	1.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	61108	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
n	23994	39.3%
o	22750	37.2%
y	4166	6.8%
e	4166	6.8%
s	4166	6.8%
u	622	1.0%
k	622	1.0%
w	622	1.0%

contact
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	210.4 KiB

cellular	18054
telephone	8862

Length

Max length	9
Median length	8
Mean length	8.329246545
Min length	8

Characters and Unicode

Total characters	224190
Distinct characters	11
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	telephone
2nd row	telephone
3rd row	telephone
4th row	telephone
5th row	telephone

Common Values

Value	Count	Frequency (%)
cellular	18054	67.1%
telephone	8862	32.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
cellular	18054	67.1%
telephone	8862	32.9%

Most occurring characters

Value	Count	Frequency (%)
l	63024	28.1%
e	44640	19.9%
c	18054	8.1%
u	18054	8.1%
a	18054	8.1%
r	18054	8.1%
t	8862	4.0%
p	8862	4.0%
h	8862	4.0%
o	8862	4.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	224190	100.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
l	63024	28.1%
e	44640	19.9%
c	18054	8.1%
u	18054	8.1%
a	18054	8.1%
r	18054	8.1%
t	8862	4.0%
p	8862	4.0%
h	8862	4.0%
o	8862	4.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	224190	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
l	63024	28.1%
e	44640	19.9%
c	18054	8.1%
u	18054	8.1%
a	18054	8.1%
r	18054	8.1%
t	8862	4.0%
p	8862	4.0%
h	8862	4.0%
o	8862	4.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	224190	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
l	63024	28.1%
e	44640	19.9%
c	18054	8.1%
u	18054	8.1%
a	18054	8.1%
r	18054	8.1%
t	8862	4.0%
p	8862	4.0%
h	8862	4.0%
o	8862	4.0%

month
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	10
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	210.4 KiB

may	8044
aug	4951
jul	4443
jun	3264
nov	3000
Other values (5)	3214

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	80748
Distinct characters	17
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	may
2nd row	may
3rd row	may
4th row	may
5th row	may

Common Values

Value	Count	Frequency (%)
may	8044	29.9%
aug	4951	18.4%
jul	4443	16.5%
jun	3264	12.1%
nov	3000	11.1%
apr	1725	6.4%
oct	521	1.9%
sep	426	1.6%
mar	410	1.5%
dec	132	0.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
may	8044	29.9%
aug	4951	18.4%
jul	4443	16.5%
jun	3264	12.1%
nov	3000	11.1%
apr	1725	6.4%
oct	521	1.9%
sep	426	1.6%
mar	410	1.5%
dec	132	0.5%

Most occurring characters

Value	Count	Frequency (%)
a	15130	18.7%
u	12658	15.7%
m	8454	10.5%
y	8044	10.0%
j	7707	9.5%
n	6264	7.8%
g	4951	6.1%
l	4443	5.5%
o	3521	4.4%
v	3000	3.7%
Other values (7)	6576	8.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	80748	100.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	15130	18.7%
u	12658	15.7%
m	8454	10.5%
y	8044	10.0%
j	7707	9.5%
n	6264	7.8%
g	4951	6.1%
l	4443	5.5%
o	3521	4.4%
v	3000	3.7%
Other values (7)	6576	8.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	80748	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	15130	18.7%
u	12658	15.7%
m	8454	10.5%
y	8044	10.0%
j	7707	9.5%
n	6264	7.8%
g	4951	6.1%
l	4443	5.5%
o	3521	4.4%
v	3000	3.7%
Other values (7)	6576	8.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	80748	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	15130	18.7%
u	12658	15.7%
m	8454	10.5%
y	8044	10.0%
j	7707	9.5%
n	6264	7.8%
g	4951	6.1%
l	4443	5.5%
o	3521	4.4%
v	3000	3.7%
Other values (7)	6576	8.1%

day_of_week
Categorical

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	210.4 KiB

thu	5663
mon	5659
tue	5258
wed	5243
fri	5093

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	80748
Distinct characters	12
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	mon
2nd row	mon
3rd row	mon
4th row	mon
5th row	mon

Common Values

Value	Count	Frequency (%)
thu	5663	21.0%
mon	5659	21.0%
tue	5258	19.5%
wed	5243	19.5%
fri	5093	18.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
thu	5663	21.0%
mon	5659	21.0%
tue	5258	19.5%
wed	5243	19.5%
fri	5093	18.9%

Most occurring characters

Value	Count	Frequency (%)
t	10921	13.5%
u	10921	13.5%
e	10501	13.0%
h	5663	7.0%
m	5659	7.0%
o	5659	7.0%
n	5659	7.0%
w	5243	6.5%
d	5243	6.5%
f	5093	6.3%
Other values (2)	10186	12.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	80748	100.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
t	10921	13.5%
u	10921	13.5%
e	10501	13.0%
h	5663	7.0%
m	5659	7.0%
o	5659	7.0%
n	5659	7.0%
w	5243	6.5%
d	5243	6.5%
f	5093	6.3%
Other values (2)	10186	12.6%

Most occurring scripts

Value	Count	Frequency (%)
Latin	80748	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
t	10921	13.5%
u	10921	13.5%
e	10501	13.0%
h	5663	7.0%
m	5659	7.0%
o	5659	7.0%
n	5659	7.0%
w	5243	6.5%
d	5243	6.5%
f	5093	6.3%
Other values (2)	10186	12.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	80748	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
t	10921	13.5%
u	10921	13.5%
e	10501	13.0%
h	5663	7.0%
m	5659	7.0%
o	5659	7.0%
n	5659	7.0%
w	5243	6.5%
d	5243	6.5%
f	5093	6.3%
Other values (2)	10186	12.6%

duration
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	1396
Distinct (%)	5.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	255.8320701

Minimum	0
Maximum	4918
Zeros	3
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	210.4 KiB

Quantile statistics

Minimum	0
5-th percentile	36
Q1	101
median	177
Q3	316
95-th percentile	747
Maximum	4918
Range	4918
Interquartile range (IQR)	215

Descriptive statistics

Standard deviation	259.1917276
Coefficient of variation (CV)	1.013132276
Kurtosis	21.5648321
Mean	255.8320701
Median Absolute Deviation (MAD)	92
Skewness	3.352341076
Sum	6885976
Variance	67180.35166
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
90	130	0.5%
73	116	0.4%
72	115	0.4%
104	114	0.4%
136	114	0.4%
124	114	0.4%
96	113	0.4%
109	109	0.4%
87	108	0.4%
126	108	0.4%
Other values (1386)	25775	95.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	3	< 0.1%
1	2	< 0.1%
3	2	< 0.1%
4	9	< 0.1%
5	18	0.1%
6	32	0.1%
7	34	0.1%
8	42	0.2%
9	52	0.2%
10	51	0.2%

Value	Count	Frequency (%)
4918	1	< 0.1%
3785	1	< 0.1%
3643	1	< 0.1%
3631	1	< 0.1%
3422	1	< 0.1%
3322	1	< 0.1%
3284	1	< 0.1%
3253	1	< 0.1%
3183	1	< 0.1%
3076	1	< 0.1%

campaign
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	41
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.570032694

Minimum	1
Maximum	56
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	210.4 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	2
Q3	3
95-th percentile	7
Maximum	56
Range	55
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	2.76312996
Coefficient of variation (CV)	1.075134167
Kurtosis	38.87088032
Mean	2.570032694
Median Absolute Deviation (MAD)	1
Skewness	4.800349514
Sum	69175
Variance	7.634887177
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=41)

Value	Count	Frequency (%)
1	11537	42.9%
2	6896	25.6%
3	3453	12.8%
4	1737	6.5%
5	1065	4.0%
6	638	2.4%
7	408	1.5%
8	263	1.0%
9	189	0.7%
10	152	0.6%
Other values (31)	578	2.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	11537	42.9%
2	6896	25.6%
3	3453	12.8%
4	1737	6.5%
5	1065	4.0%
6	638	2.4%
7	408	1.5%
8	263	1.0%
9	189	0.7%
10	152	0.6%

Value	Count	Frequency (%)
56	1	< 0.1%
43	2	< 0.1%
42	1	< 0.1%
40	2	< 0.1%
39	1	< 0.1%
37	1	< 0.1%
35	2	< 0.1%
34	3	< 0.1%
33	4	< 0.1%
32	4	< 0.1%

pdays
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	25
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	957.9719126

Minimum	0
Maximum	999
Zeros	12
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	210.4 KiB

Quantile statistics

Minimum	0
5-th percentile	999
Q1	999
median	999
Q3	999
95-th percentile	999
Maximum	999
Range	999
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	197.6440734
Coefficient of variation (CV)	0.2063151025
Kurtosis	19.25337475
Mean	957.9719126
Median Absolute Deviation (MAD)	0
Skewness	-4.609941553
Sum	25784772
Variance	39063.17974
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=25)

Value	Count	Frequency (%)
999	25804	95.9%
3	325	1.2%
6	308	1.1%
4	91	0.3%
2	48	0.2%
7	45	0.2%
9	40	0.1%
12	39	0.1%
10	34	0.1%
5	32	0.1%
Other values (15)	150	0.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	12	< 0.1%
1	20	0.1%
2	48	0.2%
3	325	1.2%
4	91	0.3%
5	32	0.1%
6	308	1.1%
7	45	0.2%
8	15	0.1%
9	40	0.1%

Value	Count	Frequency (%)
999	25804	95.9%
27	1	< 0.1%
26	1	< 0.1%
22	3	< 0.1%
21	2	< 0.1%
19	3	< 0.1%
18	5	< 0.1%
17	6	< 0.1%
16	6	< 0.1%
15	18	0.1%

previous
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	8
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.1844627731

Minimum	0
Maximum	7
Zeros	23042
Zeros (%)	85.6%
Negative	0
Negative (%)	0.0%
Memory size	210.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	1
Maximum	7
Range	7
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.5153105375
Coefficient of variation (CV)	2.793574709
Kurtosis	19.55102419
Mean	0.1844627731
Median Absolute Deviation (MAD)	0
Skewness	3.775171023
Sum	4965
Variance	0.2655449501
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
0	23042	85.6%
1	3112	11.6%
2	529	2.0%
3	163	0.6%
4	50	0.2%
5	15	0.1%
6	4	< 0.1%
7	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	23042	85.6%
1	3112	11.6%
2	529	2.0%
3	163	0.6%
4	50	0.2%
5	15	0.1%
6	4	< 0.1%
7	1	< 0.1%

Value	Count	Frequency (%)
7	1	< 0.1%
6	4	< 0.1%
5	15	0.1%
4	50	0.2%
3	163	0.6%
2	529	2.0%
1	3112	11.6%
0	23042	85.6%

poutcome
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	210.4 KiB

nonexistent	23042
failure	2864
success	1010

Length

Max length	11
Median length	11
Mean length	10.42428295
Min length	7

Characters and Unicode

Total characters	280580
Distinct characters	13
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	nonexistent
2nd row	nonexistent
3rd row	nonexistent
4th row	nonexistent
5th row	nonexistent

Common Values

Value	Count	Frequency (%)
nonexistent	23042	85.6%
failure	2864	10.6%
success	1010	3.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
nonexistent	23042	85.6%
failure	2864	10.6%
success	1010	3.8%

Most occurring characters

Value	Count	Frequency (%)
n	69126	24.6%
e	49958	17.8%
t	46084	16.4%
s	26072	9.3%
i	25906	9.2%
o	23042	8.2%
x	23042	8.2%
u	3874	1.4%
f	2864	1.0%
a	2864	1.0%
Other values (3)	7748	2.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	280580	100.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	69126	24.6%
e	49958	17.8%
t	46084	16.4%
s	26072	9.3%
i	25906	9.2%
o	23042	8.2%
x	23042	8.2%
u	3874	1.4%
f	2864	1.0%
a	2864	1.0%
Other values (3)	7748	2.8%

Most occurring scripts

Value	Count	Frequency (%)
Latin	280580	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
n	69126	24.6%
e	49958	17.8%
t	46084	16.4%
s	26072	9.3%
i	25906	9.2%
o	23042	8.2%
x	23042	8.2%
u	3874	1.4%
f	2864	1.0%
a	2864	1.0%
Other values (3)	7748	2.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	280580	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
n	69126	24.6%
e	49958	17.8%
t	46084	16.4%
s	26072	9.3%
i	25906	9.2%
o	23042	8.2%
x	23042	8.2%
u	3874	1.4%
f	2864	1.0%
a	2864	1.0%
Other values (3)	7748	2.8%

emp.var.rate
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	10
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.03275746768

Minimum	-3.4
Maximum	1.4
Zeros	0
Zeros (%)	0.0%
Negative	11775
Negative (%)	43.7%
Memory size	210.4 KiB

Quantile statistics

Minimum	-3.4
5-th percentile	-2.9
Q1	-1.8
median	1.1
Q3	1.4
95-th percentile	1.4
Maximum	1.4
Range	4.8
Interquartile range (IQR)	3.2

Descriptive statistics

Standard deviation	1.593991688
Coefficient of variation (CV)	48.66040635
Kurtosis	-1.114877951
Mean	0.03275746768
Median Absolute Deviation (MAD)	0.3
Skewness	-0.6773075169
Sum	881.7
Variance	2.540809502
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
1.4	10770	40.0%
-1.8	5808	21.6%
1.1	4371	16.2%
-0.1	2692	10.0%
-2.9	1311	4.9%
-3.4	757	2.8%
-1.7	577	2.1%
-1.1	498	1.9%
-3	125	0.5%
-0.2	7	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-3.4	757	2.8%
-3	125	0.5%
-2.9	1311	4.9%
-1.8	5808	21.6%
-1.7	577	2.1%
-1.1	498	1.9%
-0.2	7	< 0.1%
-0.1	2692	10.0%
1.1	4371	16.2%
1.4	10770	40.0%

Value	Count	Frequency (%)
1.4	10770	40.0%
1.1	4371	16.2%
-0.1	2692	10.0%
-0.2	7	< 0.1%
-1.1	498	1.9%
-1.7	577	2.1%
-1.8	5808	21.6%
-2.9	1311	4.9%
-3	125	0.5%
-3.4	757	2.8%

cons.price.idx
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	26
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	93.54073763

Minimum	92.201
Maximum	94.767
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	210.4 KiB

Quantile statistics

Minimum	92.201
5-th percentile	92.649
Q1	93.075
median	93.444
Q3	93.994
95-th percentile	94.465
Maximum	94.767
Range	2.566
Interquartile range (IQR)	0.919

Descriptive statistics

Standard deviation	0.5749010311
Coefficient of variation (CV)	0.00614599634
Kurtosis	-0.7504257313
Mean	93.54073763
Median Absolute Deviation (MAD)	0.481
Skewness	-0.1600115773
Sum	2517742.494
Variance	0.3305111956
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=26)

Value	Count	Frequency (%)
93.994	4371	16.2%
93.444	4194	15.6%
93.918	4073	15.1%
92.893	3516	13.1%
93.2	2637	9.8%
94.465	2503	9.3%
93.075	1616	6.0%
92.201	590	2.2%
92.963	574	2.1%
92.431	307	1.1%
Other values (16)	2535	9.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
92.201	590	2.2%
92.379	188	0.7%
92.431	307	1.1%
92.469	147	0.5%
92.649	262	1.0%
92.713	125	0.5%
92.756	7	< 0.1%
92.843	212	0.8%
92.893	3516	13.1%
92.963	574	2.1%

Value	Count	Frequency (%)
94.767	101	0.4%
94.601	159	0.6%
94.465	2503	9.3%
94.215	223	0.8%
94.199	238	0.9%
94.055	187	0.7%
94.027	167	0.6%
93.994	4371	16.2%
93.918	4073	15.1%
93.876	157	0.6%

cons.conf.idx
Real number (ℝ)

HIGH CORRELATION

Distinct	26
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-40.34590578

Minimum	-50.8
Maximum	-26.9
Zeros	0
Zeros (%)	0.0%
Negative	26916
Negative (%)	100.0%
Memory size	210.4 KiB

Quantile statistics

Minimum	-50.8
5-th percentile	-47.1
Q1	-42.7
median	-41.8
Q3	-36.4
95-th percentile	-31.4
Maximum	-26.9
Range	23.9
Interquartile range (IQR)	6.3

Descriptive statistics

Standard deviation	4.699283382
Coefficient of variation (CV)	-0.1164748514
Kurtosis	-0.3895031794
Mean	-40.34590578
Median Absolute Deviation (MAD)	4.4
Skewness	0.254657384
Sum	-1085950.4
Variance	22.08326431
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=26)

Value	Count	Frequency (%)
-36.4	4371	16.2%
-36.1	4194	15.6%
-42.7	4073	15.1%
-46.2	3516	13.1%
-42	2637	9.8%
-41.8	2503	9.3%
-47.1	1616	6.0%
-31.4	590	2.2%
-40.8	574	2.1%
-26.9	307	1.1%
Other values (16)	2535	9.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-50.8	101	0.4%
-50	212	0.8%
-49.5	159	0.6%
-47.1	1616	6.0%
-46.2	3516	13.1%
-45.9	7	< 0.1%
-42.7	4073	15.1%
-42	2637	9.8%
-41.8	2503	9.3%
-40.8	574	2.1%

Value	Count	Frequency (%)
-26.9	307	1.1%
-29.8	188	0.7%
-30.1	262	1.0%
-31.4	590	2.2%
-33	125	0.5%
-33.6	147	0.5%
-34.6	109	0.4%
-34.8	198	0.7%
-36.1	4194	15.6%
-36.4	4371	16.2%

euribor3m
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	309
Distinct (%)	1.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.574311785

Minimum	0.634
Maximum	5.045
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	210.4 KiB

Quantile statistics

Minimum	0.634
5-th percentile	0.755
Q1	1.334
median	4.857
Q3	4.962
95-th percentile	4.966
Maximum	5.045
Range	4.411
Interquartile range (IQR)	3.628

Descriptive statistics

Standard deviation	1.751243256
Coefficient of variation (CV)	0.4899525731
Kurtosis	-1.468188562
Mean	3.574311785
Median Absolute Deviation (MAD)	0.109
Skewness	-0.6608864608
Sum	96206.176
Variance	3.066852942
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
4.963	1777	6.6%
4.962	1703	6.3%
4.857	1636	6.1%
4.961	1114	4.1%
4.964	950	3.5%
4.965	854	3.2%
4.968	743	2.8%
1.405	741	2.8%
4.856	656	2.4%
4.076	596	2.2%
Other values (299)	16146	60.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.634	5	< 0.1%
0.635	26	0.1%
0.636	8	< 0.1%
0.637	2	< 0.1%
0.638	5	< 0.1%
0.639	6	< 0.1%
0.64	9	< 0.1%
0.642	19	0.1%
0.643	12	< 0.1%
0.644	26	0.1%

Value	Count	Frequency (%)
5.045	6	< 0.1%
5	7	< 0.1%
4.97	125	0.5%
4.968	743	2.8%
4.967	422	1.6%
4.966	488	1.8%
4.965	854	3.2%
4.964	950	3.5%
4.963	1777	6.6%
4.962	1703	6.3%

nr.employed
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	11
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5165.201445

Minimum	4963.6
Maximum	5228.1
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	210.4 KiB

Quantile statistics

Minimum	4963.6
5-th percentile	5008.7
Q1	5099.1
median	5195.8
Q3	5228.1
95-th percentile	5228.1
Maximum	5228.1
Range	264.5
Interquartile range (IQR)	129

Descriptive statistics

Standard deviation	74.60155888
Coefficient of variation (CV)	0.01444310734
Kurtosis	-0.1293520099
Mean	5165.201445
Median Absolute Deviation (MAD)	32.3
Skewness	-1.012022388
Sum	139026562.1
Variance	5565.392588
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=11)

Value	Count	Frequency (%)
5228.1	10770	40.0%
5099.1	5344	19.9%
5191	4371	16.2%
5195.8	2692	10.0%
5076.2	1311	4.9%
5017.5	757	2.8%
4991.6	577	2.1%
4963.6	498	1.9%
5008.7	464	1.7%
5023.5	125	0.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
4963.6	498	1.9%
4991.6	577	2.1%
5008.7	464	1.7%
5017.5	757	2.8%
5023.5	125	0.5%
5076.2	1311	4.9%
5099.1	5344	19.9%
5176.3	7	< 0.1%
5191	4371	16.2%
5195.8	2692	10.0%

Value	Count	Frequency (%)
5228.1	10770	40.0%
5195.8	2692	10.0%
5191	4371	16.2%
5176.3	7	< 0.1%
5099.1	5344	19.9%
5076.2	1311	4.9%
5023.5	125	0.5%
5017.5	757	2.8%
5008.7	464	1.7%
4991.6	577	2.1%

subcribed
Boolean

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	26.4 KiB

False	23621
True	3295

Common Values
Chart

Value	Count	Frequency (%)
False	23621	87.8%
True	3295	12.2%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	education	age	job	marital	default	housing	loan	contact	month	day_of_week	duration	campaign	pdays	poutcome	emp.var.rate	cons.price.idx	cons.conf.idx	euribor3m	nr.employed	subcribed
0	high.school	57	services	married	unknown	no	no	telephone	may	mon	149	1	999	nonexistent	1.1	93.994	-36.4	4.857	5191.0	no
1	high.school	37	services	married	no	yes	no	telephone	may	mon	226	1	999	nonexistent	1.1	93.994	-36.4	4.857	5191.0	no
2	high.school	56	services	married	no	no	yes	telephone	may	mon	307	1	999	nonexistent	1.1	93.994	-36.4	4.857	5191.0	no
3	professional.course	59	admin.	married	no	no	no	telephone	may	mon	139	1	999	nonexistent	1.1	93.994	-36.4	4.857	5191.0	no
4	professional.course	24	technician	single	no	yes	no	telephone	may	mon	380	1	999	nonexistent	1.1	93.994	-36.4	4.857	5191.0	no
5	high.school	25	services	single	no	yes	no	telephone	may	mon	50	1	999	nonexistent	1.1	93.994	-36.4	4.857	5191.0	no
6	high.school	25	services	single	no	yes	no	telephone	may	mon	222	1	999	nonexistent	1.1	93.994	-36.4	4.857	5191.0	no
7	high.school	29	blue-collar	single	no	no	yes	telephone	may	mon	137	1	999	nonexistent	1.1	93.994	-36.4	4.857	5191.0	no
8	high.school	30	unemployed	married	no	no	no	telephone	may	mon	38	1	999	nonexistent	1.1	93.994	-36.4	4.857	5191.0	no
9	high.school	55	retired	single	no	yes	no	telephone	may	mon	342	1	999	nonexistent	1.1	93.994	-36.4	4.857	5191.0	no

Last rows

	education	age	job	marital	default	housing	loan	contact	month	day_of_week	duration	campaign	pdays	previous	poutcome	emp.var.rate	cons.price.idx	cons.conf.idx	euribor3m	nr.employed	subcribed
26906	professional.course	57	retired	married	no	yes	no	cellular	nov	thu	124	6	999	0	nonexistent	-1.1	94.767	-50.8	1.031	4963.6	no
26907	university.degree	62	retired	married	no	no	no	cellular	nov	thu	483	2	6	3	success	-1.1	94.767	-50.8	1.031	4963.6	yes
26908	professional.course	64	retired	divorced	no	yes	no	cellular	nov	fri	151	3	999	0	nonexistent	-1.1	94.767	-50.8	1.028	4963.6	no
26909	university.degree	36	admin.	married	no	no	no	cellular	nov	fri	254	2	999	0	nonexistent	-1.1	94.767	-50.8	1.028	4963.6	no
26910	university.degree	37	admin.	married	no	yes	no	cellular	nov	fri	281	1	999	0	nonexistent	-1.1	94.767	-50.8	1.028	4963.6	yes
26911	professional.course	73	retired	married	no	yes	no	cellular	nov	fri	334	1	999	0	nonexistent	-1.1	94.767	-50.8	1.028	4963.6	yes
26912	professional.course	46	blue-collar	married	no	no	no	cellular	nov	fri	383	1	999	0	nonexistent	-1.1	94.767	-50.8	1.028	4963.6	no
26913	university.degree	56	retired	married	no	yes	no	cellular	nov	fri	189	2	999	0	nonexistent	-1.1	94.767	-50.8	1.028	4963.6	no
26914	professional.course	44	technician	married	no	no	no	cellular	nov	fri	442	1	999	0	nonexistent	-1.1	94.767	-50.8	1.028	4963.6	yes
26915	professional.course	74	retired	married	no	yes	no	cellular	nov	fri	239	3	999	1	failure	-1.1	94.767	-50.8	1.028	4963.6	no

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Other Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Other Punctuation

Dash Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Most occurring scripts

Most frequent character per script